Taxes and bank capital structure Glenn Schepens Ghent University - PowerPoint PPT Presentation

Taxes and bank capital structure Glenn Schepens Ghent University and National Bank of Belgium October 26, 2013 Disclaimer: The opinions expressed herein are solely those of the author and do not necessarily reflect those of the National Bank of Belgium.

Motivation ◮ Call for higher capital buffers vs. fear of real impact through higher funding costs ◮ Higher costs through Modigliani-Miller frictions: how important are they? Potential real impact of higher funding cost?

Motivation ◮ Call for higher capital buffers vs. fear of real impact through higher funding costs ◮ Higher costs through Modigliani-Miller frictions: how important are they? Potential real impact of higher funding cost? ◮ One frequently mentioned friction: tax shield of debt (Poole (2009), Kashyap et al. (2010),Admati et al. (2010,2013), Miles et al.(2012),...) ◮ But little empirical evidence for financial institutions! ◮ Should tax shields play a role in the capital buffer discussion? Can it serve as a policy instrument by itself?

This paper ◮ Contributes to the discussion on bank capital regulation by investigating the role of tax shields ◮ I analyze the introduction of the notional interest rate deduction (NID) in Belgium ◮ Introduced in 2006, in reaction to a ruling by the European Commission in 2003. ◮ Allows firms to deduct a notional rate on their equity ⇒ Equity funding gets subsidized, in a similar way as debt funding. ◮ The deduction equals the calculated average 10-year government bond rate of the year preceding the current fiscal year by two years. ◮ Ideal setting to study the impact of tax shields on bank capital structure.

This paper (2) ◮ I find a significant increase in equity ratios after the introduction of the NID ◮ Equity ratio is 0.91 percentage points higher compared to control group, which corresponds with an increase of around 12 percent for the average bank. ◮ Heterogeneity in treatment: more profitable banks react stronger ◮ The increase in equity ratios especially makes low-capitalized banks more stable (increase in Z-scores) ◮ Potentially interesting measure to reduce bank leverage and increase financial stability ◮ Remaining question: underlying drivers? Potential impact credit demand?

Empirical setup 1. Evolution of equity ratios in Belgium over time ◮ 35 Belgian banks, 2003-2007 ETA i , t = α i + β 1 ∗ 2006 i + β 2 ∗ 2007 i + β 3 ∗ X it + ε i , t ◮ Increase in equity ratio of 0.32 to 1.16 percentage points.

Empirical setup 1. Evolution of equity ratios in Belgium over time ◮ 35 Belgian banks, 2003-2007 ETA i , t = α i + β 1 ∗ 2006 i + β 2 ∗ 2007 i + β 3 ∗ X it + ε i , t ◮ Increase in equity ratio of 0.32 to 1.16 percentage points. 2. Difference-in-Difference analysis ◮ Match Belgian banks with a control group of European banks ◮ Use difference-in-difference setup to analyze impact of NID ETA i , t = α + β 1 ∗ Treated i + β 2 ∗ Post t + β 3 ∗ Treated i ∗ Post t + ε i , t

Matched sample Belgian Banks Non-Belgian Banks Treatment Group Full Sample Control Group Variables N Mean St. Dev. N Mean St. Dev. P-value N Mean St. Dev. P-value Equity ratio - Growth 105 -2.03 24.07 8251 2.84 20.99 0.04 315 -2.70 19.59 0.80 Equity ratio 105 7.41 7.16 8358 8.93 7.51 0.03 315 8.00 4.62 0.43 Size 105 8.40 2.23 8358 6.76 1.65 0.00 315 8.35 1.94 0.84 Profits 105 0.64 1.55 8358 0.58 1.16 0.71 315 0.71 1.03 0.65 Market share 105 0.03 0.06 8358 0.01 0.03 0.00 315 0.02 0.06 0.65 Loan ratio 105 0.37 0.22 8358 0.58 0.20 0.00 315 0.59 0.23 0.00 Non-interest income share 105 0.31 0.24 8358 0.30 0.16 0.71 315 0.32 0.15 0.54 Non-performing loans 105 0.34 0.35 8340 0.30 0.36 0.21 315 0.34 0.25 0.91 Risk 96 0.49 0.79 8038 0.24 0.44 0.00 315 0.36 0.48 0.11 Propensity score matching procedure to 1) come as close as possible to common trend assumption and 2)to reduce probability that differences along unobservables invalidate diff-in-diff.

Equity ratios - Belgium vs. control group 9.00 8.50 8.00 7.50 7.00 6.50 2002 2003 2004 2005 2006 2007 Control BE

Difference-in-Difference - Results (1) (2) (3) VARIABLES ETA Average ETA ETA Post -0.516* -0.361 -0.238 (0.286) (0.241) (0.273) Treated x Post 0.910** 0.838** 0.807* (0.424) (0.346) (0.463) Constant 7.851*** 7.714*** 21.95*** (0.0915) (0.135) (4.660) Observations 700 280 648 Adjusted R-squared 0.842 0.901 0.858 Bank FE Yes Yes Yes Clusterlevel Bank Bank Bank Bank control variables No No Yes Country control variables No No Yes Robust standard errors in parentheses

Results ◮ Strong increase in equity ratio of Belgian banks after introduction NID ◮ Average 2007 equity ratio is 1.17 percentage points higher than the pre-treatment average . ◮ Diff-in-diff shows that average Belgian equity ratio increased by 0.91 percentage points, which equals a 12 percent increase for the average Belgian bank. ◮ Robust to alternative matching procedure (number of matches/matching variables), sample selection issues, controlling for country/bank characteristics in diff-in-diff,...

Empirical difficulties - confounding shocks ◮ Results are not influenced by time-invariant bank heterogeneity or permanent differences between treatment and control group ⇒ Treatment dummy/bank fixed effects

Empirical difficulties - confounding shocks ◮ Results are not influenced by time-invariant bank heterogeneity or permanent differences between treatment and control group ⇒ Treatment dummy/bank fixed effects ◮ Results are not influenced by trends common to treatment and control group

Empirical difficulties - confounding shocks ◮ Results are not influenced by time-invariant bank heterogeneity or permanent differences between treatment and control group ⇒ Treatment dummy/bank fixed effects ◮ Results are not influenced by trends common to treatment and control group ◮ Results are unlikely to be influenced by variation in post-treatment (observable) bank characteristics ⇒ Control for bank characteristics in diff-in-diff regressions in diff-in-diff regressions

Empirical difficulties - confounding shocks ◮ Results are not influenced by time-invariant bank heterogeneity or permanent differences between treatment and control group ⇒ Treatment dummy/bank fixed effects ◮ Results are not influenced by trends common to treatment and control group ◮ Results are unlikely to be influenced by variation in post-treatment (observable) bank characteristics ⇒ Control for bank characteristics in diff-in-diff regressions in diff-in-diff regressions ◮ Results could be sensitive to contemporaneous events that have a differential impact across countries

Increasing ECB rate ◮ Increase in ECB policy rate between 2006- mid-2008 ⇒ Exactly our treatment period! ◮ Cross-country heterogeneity in pass-through of MP : Higher market concentration / market power → slower pass through (e.g. Van Leuvensteijn et al. (2007), Kok and Werner (2006), De Graeve et al. (2007)) ◮ Could impact denominator of equity ratio and bias our analysis ⇒ Three robustness checks

Increasing ECB rate - Robustness 1. Between country test - Placebo analysis - similar increase in ECB rate in 2000 : No impact ETA Average ETA Post -0.0137 -0.150 (0.301) (0.260) Treated x Post 0.162 0.328 (0.439) (0.379) Observations 700 548 Adjusted R-squared 0.842 0.893 Bank FE Yes Yes Clusterlevel Bank Bank

Increasing ECB rate - Robustness 2. Between country test - Belgian market concentration on average higher than in control sample ⇒ Should thus work against us - potentially too conservative

Increasing ECB rate - Robustness 3. Within country test - higher impact on banks with high market share? 2000 Placebo Market Share ETA Average ETA ETA Post -0.0137 -0.150 -0.449 (0.301) (0.260) (0.322) Treated x Post 0.162 0.328 0.889* (0.439) (0.379) (0.490) Treated x Post x Variable -0.0104 (0.0750) Observations 700 548 700 Adjusted R-squared 0.842 0.893 0.842 Bank FE Yes Yes Yes Clusterlevel Bank Bank Bank

Risk profile ◮ Low vs. High capitalized banks (1) (2) (3) (4) (5) (6) VARIABLES ETA ETA Z-score Z-score σ ( ROA ) σ ( ROA ) Post -0.516* -0.386* 0.0350 -0.112 -0.0758** -0.0278 (0.286) (0.233) (0.105) (0.160) (0.0383) (0.0539) Treated x Post 0.910** 0.823* 0.157 0.689* 0.0502 -0.191 (0.424) (0.432) (0.299) (0.369) (0.142) (0.130) Treated x Post x ETA-high 0.175 -1.058* 0.476* (0.856) (0.578) (0.272) Constant 7.851*** 7.851*** 3.712*** 3.709*** 0.389*** 0.390*** (0.0915) (0.0915) (0.0440) (0.0428) (0.0186) (0.0179) ◮ Low cap banks ⇒ Stronger increase in Z-score!

Conclusions ◮ I analyze the introduction of the notional interest rate deduction (NID) in Belgium ◮ Introduced a tax shield for equity ◮ Belgian equity ratios are significantly higher in 2006-2007, rising between 32 and 117 percentage points. ◮ Difference-in-difference analysis: Equity ratio for the average Belgian bank increases with 12 percent. ◮ More profitable banks show a stronger increase - more sensitive to tax shields. ◮ low capitalized banks become more stable. ◮ Tax shields do impact bank capital structures. ◮ Reduction of tax discrimination could potentially be used as a policy tool.